Wearables are expected to grow rapidly in the coming years — according to market research, the space is growing at greater than 20% annually and is expected to hit a market size of 150 billion EUR by 2028. Wearables have come a long way in being more accessible and feature rich. For reference, consumers can buy fitness trackers equipped with multiple sensors and advanced tracking for as little as $100, such as the FitBit Inspire 3, whereas 50 years ago, a simple watch with a calculator could cost several thousands of dollars (e.g., the Pulsar Calculator Watch in 1975 — for more on the history of wearables, check out: A Guided History of Wearable Devices). There are many factors that helped make wearables more commonplace such as the miniaturization of technology, increased computation, and less expensive hardware.
The growth of wearables is also driven by adjacent technologies because wearables leverage a variety of tools and strive to deliver many features. In this article, we’ll discuss how the growth in Artificial Intelligence / Machine Learning (AI / ML), Internet of Things (IoT), and faster internet / edge computing help to advance wearables.
(Note: this article is not exhaustive on all the adjacent technology helping to advance wearables; other adjacent technologies are improved battery technology, advancements in materials / manufacturing, sensor development, etc.).
Artificial Intelligence / Machine Learning (AI / ML)
Wearable devices collect a lot of data on users — according to Statista, it is estimated that 335 petabytes of data is collected per month from wearables in 2020. This data helps to fuel AI / ML systems, which make decisions based on data, to produce meaningful metrics and predictions for users. Many wearables nowadays go beyond just tracking your data, but also providing “scores” and making predictions. For example, WHOOP, a fitness tracker geared toward athletic performance and recovery, has a recovery and strain metric and determines irregularities customized to the user’s baseline.
There’s a lot of advancements in AI / ML, from better performing algorithms to faster implementations, which help to make wearables more feature rich. Wearables leveraging camera or computer vision can utilize object detection, localization, and segmentation to assess their environments / users such as the OrCam MyEye 2.0 which can identify text and read it aloud for visually impaired individuals. Advancements in Natural Language Processing can help to create better assistants that can be onboard wearable devices such as Siri on the Apple Watch. And reinforcement learning can be used to inform when best to execute certain actions (such as alerts or notifications) such as with just-in-time adaptive interventions for optimizing physical health. There are many more applications of AI / ML in the wild and being developed to make wearables more functional and smart.
Internet of Things (IoT)
The Internet of Things refers to the expanding network of electronic devices, sensors, and software that communicate and interact with each other. Wearable devices are part of the IoT space. A notable example of wearable devices interacting with other IoT technologies is the Apple ecosystem. The Apple Watch integrates with other Apple accessories, letting users to take interactions with their wearable watch to their own Apple devices. Furthermore, with the Home app, the Apple Watch can also potentially integrate with home accessories such as lights, locks, smart TVs, thermostats, window shades, and smart plugs.
With more development in the IoT space, the number of smart devices that can be connected to wearable devices will increase. Coupled with AI / ML, these IoT interactions can be further automated based on data collected on the user. An example of this is auto-adjusting air conditioning based on temperature sensor readings. Furthermore, the interaction of other IoT devices to the wearable is another popular use-case, where users can receive inputs to their wearables based on other devices. For the wearable space, IoT has and will continue to open new features / capabilities.
Faster Internet / Edge Computing
The last technology we’ll cover is faster Internet. This is being developed in two main forms: infrastructure investment and wireless technology.
Governments are recognizing the importance of high speed, low latency internet, especially in the wake of the COVID pandemic, where the world had to go remote. In the United States, the Bipartisan Infrastructure Law (BIL) (also called the Infrastructure Investment and Jobs Act (IIJA)) has allocated millions of dollars to establish better, high speed internet access across the country. This endeavor is expected to take 5 years to complete and will provide internet for millions of Americans.
In addition, telecommunications companies (such as AT&T and Verizon) are investing in 5G wireless infrastructure. In a nutshell, 5G wireless is the latest wireless standard that promises to deliver higher speed, lower latency, and expanded network capacity with greater reliability. More information on 5G technology can be found here: 5G Technology and Applications.
Faster internet can enable greater functionality for wearables, through edge computing, which refers to performing complex tasks on the cloud in (near) real-time. Examples of such tasks include data processing, real-time / online machine learning, and predictive analysis. Edge computing takes the computational burden off from the device and moves it to remote servers with better hardware / greater computational power. This would allow wearables to have less computational components, leverage more sophisticated machine learning algorithms, and reduce power consumption. As a result, wearables can become faster, sleeker, and higher-performing with edge computing. However for wearables to reliably leverage edge computing, better internet infrastructure will be needed. Hopefully, with investments in making high speed, low latency internet and 5G wireless, edge computing will become more utilized in wearables.
Conclusion
Wearables is a rapidly growing field and can potentially transform how our society interacts with technology. Alongside wearables, several key adjacent technologies are empowering their development — in this article, we looked at AI / ML, IoT, and faster internet / edge computing and their role in wearable devices. As these adjacent fields develop, we will see them being integrated with wearable devices, making them more accessible and functional.
For more on this topic, check out: A Guided History of Wearable Devices
